IMPROVE THE PERFORMANCE OF AODV UNDER BLACKHOLE ATTACK IN MANET

The Mobile Ad-hoc Network is an infrastructure-less network in which each mobile node can communicate with other node without any fixed network. In view of this, the networks are vulnerable to various kind of attacks such as black hole attack, gray hole attack etc. The black hole attack is one of the cruel attacks in Mobile Ad-hoc NETwork (MANET). The simulation is carried out using MATLAB and analyzes the black hole attack in Ad-hoc On-demand Distance Vector (AODV) routing protocol and compared the performance of packet delivery ratio and delay with existing algorithm Hash_DSR. The result shows that the Hash_AODV is better than the Hash_DSR

Utilizing the protected learning calculation method to forestall the Black Hole Attacks in Mobile ad-hoc networks

Mobile Ad-hoc Networks (MANETs) are a gathering of portable hosts which speak with each other with no focal system power or altered foundation. Because of its attributes like portability furthermore, heterogeneity ad-hoc networks are more defenseless to assaults. Black hole is an assault where every one of the bundles sent to assailant hub, by neighboring hubs, are dropped purposefully. In this thesis, we propose a secure learning calculation method which intends to identify and securing the black hole by considering the bundle drop reasons in needless mode. Presented AODV direction convention is adjusted to distinguish and securing the black hole assault. The investigation results demonstrate that our proposed calculation secure the AODV against black hole assault in MANETs

Eaodv: A*-based Enhancement Ad-hoc on Demand Vector Protocol to Prevent Black Hole Attacks

Black hole attack is an attack where a node that responds to RREQ from the source node by replying a fake freshness information and false hop count. The black hole nodes do not respond to distributed co-operation in routing protocol to absorb all the packets, as a result, the network performance will drop. Most previous works are focused on anomaly detection through dynamic trusted of the neighbouring nodes. We find out that the internal comparisons take a long time. This loss can be shortened by changing the routing mechanism. We propose an enhancement of AODV protocol, named EAODV, that is able to prevent black hole attacks. The EAODV can find a shortest path of routing discovery using A* heuristic search algorithm. Values of hop count and estimate time to reach the destination node are used as input in the heuristic equation and one-way hash function is used to make a secure value and then to casting it to all neighbouring nodes. Experiments were conducted in NS2 to simulate EAODV in different running time with and without black hole nodes. The EAODV performance results are indicated better in terms Packet loss and Average End-to-End delay

A parallel prevention algorithm for black hole attacks in MANET

In this paper, we propose a parallel algorithm for MANETs that optimizes both routing discovery and security in an Ad Hoc On Demand Distance Vector (AODV). The new algorithm, termed as Parallel Grid Optimization by the Daddy Long-Legs Algorithm (PGO-DLLA), simulates the behavior of the biological spiders known as daddy long-legs spiders.Experiments were conducted on an NS2 simulator to demonstrate the efficiency and robustness of the proposed algorithm.The results indicate better performance than the AntNet algorithm with respect to all metrics that used in experiments such as packet delivery ratio (PDR), end-to-end delay (EtoE) and Packet loss (PL) except throughput, for which AntNet is the better algorithm.In addition, the results show that PGO-DLLA outperforms the standard AODV algorithm in simulations of both a peaceful environment and a hostile environment represented by a black hole attacks

Protocol for Multiple Black Hole Attack Avoidance in Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) form a new wireless networking paradigm with unique characteristics that give them appreciated interest in a vast range of applications. However, many challenges are facing MANETs including security, routing, transmission range, and dynamically changing topology with high node mobility. Security is considered as the main obstacle for the widespread adoption of MANET applications. Black hole attack is a type of DoS attack that can disrupt the services of the network layer. It has the worst malicious impact on network performance as the number of malicious nodes increases. Several mechanisms and protocols have been proposed to detect and mitigate its effects using different strategies. However, many of these solutions impose more overhead and increase the average end-to-end delay. This chapter proposes an enhanced and modified protocol called “Enhanced RID-AODV,” based on a preceding mechanism: RID-AODV. The proposed enhancement is based on creating dynamic blacklists for each node in the network. Each node, according to criteria, depends on the number of mismatches of hash values of received packets as compared with some threshold values, and the sudden change in the round-trip time (RTT) can decide to add or remove other nodes to or from its blacklist. The threshold is a function of mobility (variable threshold) to cancel the effect of normal link failure. Enhanced RID-AODV was implemented in ns-2 simulator and compared with three previous solutions for mitigating multiple black hole attacks in terms of performance metrics. The results show an increase in throughput and packet delivery ratio and a decrease in end-to-end delay and overhead ratio